Quantum Motion, a UK-based quantum computing company, and Goldman Sachs have developed a quantum algorithm aimed at improving options pricing for financial services. This algorithm, which handles complex, multi-qubit operations essential for such calculations, is designed to enhance both speed and accuracy. The research titled “Low Depth Phase Oracle Using a Parallel Piecewise Circuit”, now published on the arXiv, evaluates how quantum algorithms could streamline options pricing by processing extensive market data and rapidly simulating numerous scenarios.
The collaboration has focused on optimizing quantum software for use on hardware with limited qubit counts, a common constraint in current quantum systems. Quantum Motion’s approach involves dividing algorithms into smaller, parallel tasks, maximizing qubit usage and reducing calculation time. This method could provide the response times necessary for practical applications in time-sensitive fields like finance.
Beyond finance, the algorithm design also holds promise for applications in chemistry and materials science, with the paper detailing an approach to simulate Coulomb potentials in quantum systems. This capability is significant for studying molecular interactions and developing new materials.
Quantum Motion’s strategy centers on building scalable quantum chips, leveraging silicon-based architectures compatible with conventional semiconductor technology. Partnering with Goldman Sachs has enabled the team to tailor its technology for real-world, high-impact applications, aligning quantum development with specific industry requirements.
For additional information, refer to Quantum Motion’s press release here.
November 1, 2024
